DBMS > Atos Standard Common Repository vs. MonetDB vs. OpenTSDB vs. WakandaDB

System Properties Comparison Atos Standard Common Repository vs. MonetDB vs. OpenTSDB vs. WakandaDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A relational database management system that stores data in columns

Scalable Time Series DBMS based on HBase

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.monetdb.org

opentsdb.net

wakanda.github.io

Technical documentation

www.monetdb.org/Documentation

opentsdb.net/docs/build/html/index.html

wakanda.github.io/doc

Developer

Atos Convergence Creators

MonetDB BV

currently maintained by Yahoo and other contributors

Wakanda SAS

Initial release

2016

2004

2011

2012

Current release

1703

Dec2023 (11.49), December 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

LGPL

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, JavaScript

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

numeric data for metrics, strings for tags

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

LDAP

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP API
Telnet API

RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Erlang
Go
Java
Python
R
Ruby

JavaScript

Server-side scripts

Stored procedures

yes, in SQL, C, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding via remote tables

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

LDAP bind authentication

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

Recent citations in the news

MonetDB Foundation launched
31 January 2024, Centrum Wiskunde & Informatica (CWI)

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R — Part I
6 April 2018, Data Science Central

How MonetDB/X100 Exploits Modern CPU Performance
14 January 2020, Towards Data Science

Test of Time Award for paper on vectorized execution
16 January 2024, Centrum Wiskunde & Informatica (CWI)

Monet DB The Column-Store Pioneer
4 September 2019, Open Source For You

provided by Google News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

A real-time processing revival
1 April 2015, O'Reilly Media

provided by Google News

Share this page